One of the advantages that digital photography has over traditional film-based photography is that digital images can be further processed even after the camera has taken and stored the image. Because the digital image is stored as digital data that fully describes the digital image, digital processing can be used to manipulate that data in a wide variety of ways. Such processing can include color adjustment or enhancement, filtering (such as blurring), image size adjustment, cropping, and a variety of other processing techniques.
Due to the wide variability of digital images, however, digital image processing is often a very manual and time consuming process. Examples of such variability include differences in color or brightness, and differences in the position or size of the subject within the digital images. Although various tools are available to assist the operator in processing the digital data, the tools generally require the operator to selectively apply the various processes based on the unique characteristics of a particular image. The deficiencies of existing tools are particularly pronounced when large volumes of digital images need to be processed.
Further, because of the manual nature of such image processing tools, the final results are often inconsistent and variable. Such variability is particularly undesirable when a composite product (such as a school yearbook or photo directory) is produced including arrangements of multiple digital images. The lack of uniformity of the images in such products can be very noticeable when arranged in this manner.
Therefore, there is a need for systems and methods for improving the automation of digital image processing, such as to reduce the amount of manual effort required to process the digital images, and to produce final images having improved uniformity and consistency.